Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

Identifying Threshold of Social Influences on Lifetime Smoking Status - A Recursive Partitioning Approach

1.606 visualizaciones

Publicado el

How many smoker friends one "needs" to have to be considered as at a substantial risk of becoming a smoker him/herself?

Publicado en: Salud y medicina
  • Sé el primero en comentar

  • Sé el primero en recomendar esto

Identifying Threshold of Social Influences on Lifetime Smoking Status - A Recursive Partitioning Approach

  1. 1. Identifying Threshold of Social Influences on Lifetime Smoking Status among Adolescents – A Recursive Partitioning Approach Yue Liao, MPH Jimi Huh, PhD Zhaoqing Huang, MD, MA Arif Ansari, PhD Mary Ann Pentz, PhD Chih-Ping Chou, PhD Presented at the 33rd Annual Meeting of the Society of Behavioral Medicine April, 2012 Contact: yueliao@usc.edu
  2. 2. Social Influences and Cigarette Smoking • Adolescents’ cigarette smoking behavior is affected by the ones of their friends and parent • peer influences are believed to be the most significant psychosocial risk factors for cigarette smoking • parental behavior may have different degree of influence on child at different agesAvenevoli & Merikangas, 2003; Kobus, 2003; Hoffman et al., 2006; Darling & Cumsille, 2003 2
  3. 3. • Combined effects of peer and parental influences • Non-smoking parents had a buffering effects on peer influencesLi, Pentz, & Chou, 2002 3
  4. 4. • However, the threshold of such effects have not yet been well examined • i.e., how many smoker friends one “needs” to have to be considered as a substantial risk factor• Combinations of peer and parental influences with different thresholds? • May be useful to identify high-risk groups 4
  5. 5. Current Study• To identify combinations and thresholds of social influences variables that predict lifetime smoking status among adolescents 5
  6. 6. Participants• 1,073 students from the Midwestern Prevention Project • a longitudinal study that followed participants yearly from 6th/7th to 12th grade• Students were from Indianapolis, IN • 48.7% male, 76.0% Caucasian • 33.6% from low socioeconomic status family • 74.8% from public schools • 48.6% in the intervention group 6
  7. 7. Social Influence Variables• Peer influences • perceived friend use (1-7) • “How many of your close friends use cigarettes?” • perceived social norms (1-10) • “Out of every 100 students in your age, how many do you think smoke cigarettes at least once a month?”• Parental influences • perceived parent use (0-2) • “How many of the two important adults in your life use cigarettes” 7
  8. 8. • Responses from 6th/7th to 8th grade were averaged to represent social influence during middle/junior high school (JHS) period• Responses from 9th to 12th grade were averaged to represent high school (HS) period 8
  9. 9. Lifetime Smoking Status• Students were considered as “lifetime non- smokers” if • selected “none” or “one puff to one cigarette” to the question • “How many cigarettes have you smoked in your whole life?” • at each wave of the surveys• At 12th grade, 29.7% of the students were identified as “lifetime non-smokers” 9
  10. 10. Statistical Methods• Recursive partitioning was used to classify membership (lifetime smokers vs. non- smokers) based on social influences & demographic variables • a binary classification method that creates a decision tree • can examine the effects of combination of multiple predictors • if a person has x, y, and z, what is the probability of having condition q 10
  11. 11. • Combination of the predictors and the associated cut-point was selected based on conditional probability that can minimize the entropy (randomness) in the model• Analysis was performed using JMP 9.0.0 11
  12. 12. Results• 13 groups with different combinations of social influences and demographic variables that distinguish between lifetime smokers vs. non-smokers were identified• Accuracy rate of predicting smokers vs. non-smokers was 76.5% 12
  13. 13. 13
  14. 14. 14
  15. 15. Combinations of factors that predict lifetime Probabilitsmokers y1. Have >=8 smoker friends during HS (N=124) 96.57%2. Have 3-7 smoker friends during HS + White + No 95.96% intervention (N=55)3. Have 2 smoker friends during HS + >=1 smoker friends 92.27% during JHS + Non-White (N=16)Combinations of factors that predict lifetimenon-smokers1. Have no smoker friends during JHS + no smoker friends 77.06% during HS + <2 smoker parent (N=54)2. Have no smoker friends during JHS + >=1 smoker friends 76.23% during HS + norms during HS >=47.5% + Non-White + no smoker parent (N=10)3. Have no smoker friends during JHS + >= 1 smoker friends 76.13% 15 during HS + norms during HS <47.5% (N=31)
  16. 16. Conclusions• Threshold of peer influences • having 2+ smoker friends during HS gives high probability of being smokers • having no smoker friends during JHS gives high probability of being non-smokers• Threshold of parental influences • having 1 or less smoker parent gives high probability of being non-smokers 16
  17. 17. Limitations• Self-reported measures• Reduced variations of social influences factors by using averages across waves• Use of only perceived friend use, social norms, and parent use to represent social influences 17
  18. 18. Implications• Interventions start at junior high school to prevent students becoming cigarette smokers • counteract the social influences from peers and parents• Interventions target high-risk group • high school students who have 2+ smoker friends 18
  19. 19. Acknowledgments• Funded by NIH R01DA027226 (Chou, PI) 19

×